Please wait a minute...
Vis Inf  2019, Vol. 3 Issue (1): 1-8    DOI: 10.1016/j.visinf.2019.03.001
论文     
aflak:一个在分析天文数据集时支持端到端起源管理的可视化编程环境
Malik Olivier Boussejraa, Rikuo Uchikia, Yuriko Takeshimab, Kazuya Matsubayashic, Shunya Takekawad, Makoto Uemurae, Issei Fujishiroa
aKeio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Kanagawa, Japan  bTokyo University of Technology, 1404-1 Katakuramachi, Hachiō,ji, Tokyo, Japan  cKyoto University, 3037-5 Honjo, Kamogata, Asakuchi, Okayama, Japan  dNobeyama Radio Observatory, National Astronomical Observatory of Japan, 462-2 Nobeyama, Minamimaki, Minamisaku-gun, Nagano, Japan eHiroshima University, 1-3-2 Kagamiyama, Higashi-Hiroshima, Hiroshima, Japan
aflak: Visual Programming Environment Enabling End-to-End Provenance Management for the Analysis of Astronomical Datasets
Malik Olivier Boussejraa, Rikuo Uchikia, Yuriko Takeshimab, Kazuya Matsubayashic, Shunya Takekawad, Makoto Uemurae, Issei Fujishiroa
aKeio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Kanagawa, Japan  bTokyo University of Technology, 1404-1 Katakuramachi, Hachiō,ji, Tokyo, Japan  cKyoto University, 3037-5 Honjo, Kamogata, Asakuchi, Okayama, Japan  dNobeyama Radio Observatory, National Astronomical Observatory of Japan, 462-2 Nobeyama, Minamimaki, Minamisaku-gun, Nagano, Japan eHiroshima University, 1-3-2 Kagamiyama, Higashi-Hiroshima, Hiroshima, Japan
 全文: PDF 
摘要: 本文描述了一个可扩展的图形框架aflak,它能够为多光谱天文数据集的分析提供了可视和起源管理平台。 通过aflak的结点编辑器界面,天文学家可以对从公共天文数据库输入的可查询的数据集进行变换,然后将分析结果导出为FITS图像传输系统文件,可使输出数据的全部来源得以保存和便于检查,能为常见的天文分析软件所采用。 FITS是天文学中数据交换的标准。 把aflak的起源数据嵌入到FITS文件中,我们既能与现有软件互联互通,又可以完整地重现天文学家的发现过程。
关键词: 天文学出处可视化编程可视化    
Abstract: This paper describes an extendable graphical framework, aflak, which provides a visualization and provenance management environment for the analysis of multi-spectral astronomical datasets. Via its node editor interface, aflak the astronomer to compose transforms on input datasets queryable from public astronomical data repositories, then to export the results of the analysis as Flexible Image Transport System (FITS) files, in a manner such that the full provenance of the output data be preserved and reviewable, and that the exported file be usable by other common astronomical analysis software. FITS is the standard of data interchange in astronomy. By embedding aflak’s provenance data into FITS files, we both achieve interoperability with existing software and full reproducibility of the process by which astronomers make discoveries.
Key words: Astronomy    Provenance    Visual Programming    Visualization
出版日期: 2019-04-17
通讯作者: Malik Olivier Boussejra     E-mail: malik@boussejra.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
Malik Olivier Boussejra
Rikuo Uchiki
Yuriko Takeshima
Kazuya Matsubayashi
Shunya Takekawa
Makoto Uemura
Issei Fujishiro

引用本文:

Malik Olivier Boussejra, Rikuo Uchiki, Yuriko Takeshima, Kazuya Matsubayashi, Shunya Takekawa, Makoto Uemura, Issei Fujishiro. aflak: Visual Programming Environment Enabling End-to-End Provenance Management for the Analysis of Astronomical Datasets. Vis Inf, 2019, 3(1): 1-8.

链接本文:

http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2019.03.001        http://www.zjujournals.com/vi/CN/Y2019/V3/I1/1

[1] Shahid Latif, Fabian Beck. 概述双变量地理数据的交互式地图报告[J]. Vis Inf, 2019, 3(1): 27-37.
[2] Mohammad Chegini, Jürgen Bernard, Philip Berger, Alexei Sourin, Keith Andrews, Tobias Schreck. 使用链接可视化,聚类和主动学习对监督机器学习进行多变量数据集的交互式标记[J]. Vis Inf, 2019, 3(1): 9-17.
[3] Chong Zhang, Yang Chen, Jing Yang, Zhengcong Yin. 一种基于关联规则的减少平行集视觉混乱的方法[J]. Vis Inf, 2019, 3(1): 48-57.
[4] Roger Almeida Leite, Theresia Gschwandtner, Silvia Miksch, Erich Gstrein, Johannes Kuntner. 采用可视化分析来检测欺诈事件 [J]. Vis Inf, 2018, 2(4): 198-212.
[5] Jenny Vuong, Sandeep Kaur, Julian Heinrich, Bosco K.Ho, Christopher J.Hammang, Benedetta F.Baldi, Seán I.O’Donoghue. Versus——使用2AFC方法评估可视化和图像质量的工具[J]. Vis Inf, 2018, 2(4): 225-234.
[6] Aindrila Ghosh, Mona Nashaat, James Miller, Shaikh Quader, Chad Marston. 面向表格式工业数据集的探索性分析工具综述[J]. Vis Inf, 2018, 2(4): 235-253.
[7] Vahan Yoghourdjian, Daniel Archambault, Stephan Diehl, Tim Dwyer, Karsten Klein, Helen C.Purchase, Hsiang-Yun Wu. 探索复杂性的极限:图可视化实例研究综述[J]. Vis Inf, 2018, 2(4): 264-282.
[8] Takanori Fujiwara, Tarik Crnovrsanin, Kwan-Liu Ma. 交互式网络分析过程的简明概括  [J]. Vis Inf, 2018, 2(4): 213-224.
[9] Rulei Yu, Lei Shi. 深度学习可视化综述:面向用户群体分类 [J]. Vis Inf, 2018, 2(3): 147-154.
[10] Indratmo, LeeHoworko, Joyce MariaBoedianto, BenDaniel. 采用堆叠条形图进行单个属性和整体属性比较的有效性 [J]. Vis Inf, 2018, 2(3): 155-165.
[11] Christopher Collins, Natalia Andrienko, TobiasSchreck, JingYang, Jaegul Choo, Ulrich Engelke, Amit Jena, Tim Dwyer. 人机分析过程导引 [J]. Vis Inf, 2018, 2(3): 166-180.
[12] DeqingLi, HonghuiMei, YiShen, ShuangSu, WenliZhang, JuntingWang, MingZu, WeiChen. ECharts: 是一款开源的、基于 web 的、跨平台的支持快速创建交互式可视化的框架[J]. Vis Inf, 2018, 2(2): 136-146.
[13] Maha El Meseery, Orland Hoeber. 地理协同平行坐标(GCPC):环境数据分析的现场试验研究 [J]. Vis Inf, 2018, 2(2): 111-124.
[14] Yusuke Ishikawa, Issei fujishiro. TideGrapher:橄榄球比赛战术的可视分析[J]. Vis Inf, 2018, 2(1): 60-70.
[15] Christina Gillmann, Robin G.C. Maack, Tobias Post, Thomas Wischgoll, Hans Hagen. 在知晓其不确定性的情况下运用分层图像语义进行锁孔手术规划的工作流程[J]. Vis Inf, 2018, 2(1): 26-36.